3. The analytical model

and simulation results are presented in Section 6. In this section we validate our

The performance of the MAC sublayer in IEEE802.15.4 standard has been evaluated in the literature. The crowd of earlier investigations was based upon MAC sublayer simulation. Lu et al., [24] and Zheng and Lee [25] performed their research

Gradually, analytical models emerged in this research area where Cao et al., [26]

presented an analytical model which was only able to calculate the throughput. Some other models were only able to calculate the energy like [27]. Furthermore, with the passage of time, Markov chain analytical models were proposed, the

It should be also pointed out that Bianchi's model [28] was not proper for IEEE802.15.4 standard due to the different functionalities of CSMA/CA mechanism

In [14], although the authors presented an analytical Markov model to evaluate MAC sublayer in the presence of uplink and downlink saturated traffic, the model

In 2009, despite Yung's efforts to consider retransmission in their proposed

In more developed models, Faridi et al., [29] employed retransmission, packet

In [30], a Markov model is provided to evaluate MAC sublayer and calculate the delay, energy, and throughput which suffers from some drawbacks. Not only did they assume unsaturated data, but they also considered predetermined length for the idle state. In our work, we demonstrate that the duration of the idle states depends on the instantaneous network conditions which might obviously change by

Owing to this point, we have considered a variable duration of idle states in our

In [31], the authors used a model focused on CAP (contention access period), to

In spite of some drawbacks such as the lack of any queues and some problems in the modeling of the idle states, Park [16, 32] developed the model proposed in [14] through adding retransmission in several investigations. In effect, in Park's model, before passing the whole period of idle states' duration, no node is allowed to leave the idle state, when a new packet is generated. In addition, Park [32] used a backoff with duration of 305 μs instead of the 320 μs, which leads to inaccuracy in his experimental tests. In our experiment, a 1 MHz hardware timer

In [33], the authors provided different services in Smart Grid by introducing of delay-responsive cross layer (DRX) and also prioritizing input data. DRX classifies information into two categories in the application layer. Potential delay is calculated for every input packet regarding the network history. Then, the best decision was

calculate the throughput and energy and evaluate the effects of a finite length

is utilized, to enhance timer resolution up to 1 μs and applying 320 μs to

taken at the MAC sublayer to achieve minimum delay to send the packet.

analysis by experimental results and Monte Carlo simulations. Finally,

Section 7 concludes the paper.

Research Trends and Challenges in Smart Grids

2. Related works

based upon simulation.

passing of time.

aUnitBackoffPeriod.

78

buffer on network performance.

majority of which are based on [28]'s results.

in IEEE 802.11 and IEEE802.15.4 standards.

model, packet length and acknowledgment were ignored.

proposed model to deal with the changes in network condition.

length, and acknowledgment in their advanced model.

suffers from the lack of retransmission.

In this section, an accurate analytical model is proposed for industrial applications as well as Smart Grids.

IEEE802.15.4 specifies physical and MAC layers, a low-rate and low-energy consumption solution [10]. This standard provides two channel access types: slotted CSMA/CA and unslotted CSMA/CA [34, 35]. Further information concerning the standard for enthusiastic readers is in [36–38].

In order not to get involved in useless elaborate calculations, we consider a star topology with a PAN coordinator, N nodes, and the slotted beacon-enabled CSMA/ CA mechanism. Acknowledgment is enabled, and a MAC sublayer buffer has also been designed. The input traffic can be saturated, but its distribution is deterministic. We also assume that the arrival rates for all nodes are the same, and nodes start sensing the medium independently. Table 2 shows the summary of notations we use in our equations and diagrams.


Table 2. Summary of notations.
